Azure Databricks with Pyspark Course Overview

Azure Databricks with Pyspark Course Overview

Unlock the power of big data processing with our Azure Databricks with Pyspark course. This comprehensive training equips you with essential skills in data analysis, machine learning, and data engineering using Azure Databricks and Pyspark. Participants will master key concepts, including Spark architecture, data manipulation, and distributed computing, all tailored for practical application in real-world scenarios.

By the end of the course, you will confidently be able to process large datasets, develop scalable data pipelines, and implement machine learning models. Join us to enhance your data analytics capabilities and gain hands-on experience that will significantly impact your career in the tech industry.

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2,250

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Course Fee 2,250
Total Fees
2,250 (USD)
  • Live Training (Duration : 60 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request

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  • Live Training (Duration : 60 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Target Audience for Azure Databricks with Pyspark

Azure Databricks with Pyspark is a comprehensive course designed to empower professionals with the skills needed to harness the power of big data analytics in the cloud.


  • Data Scientists
  • Data Engineers
  • Business Intelligence Analysts
  • Cloud Solutions Architects
  • Software Developers
  • Machine Learning Engineers
  • Database Administrators
  • IT Project Managers
  • Data Analysts
  • System Administrators
  • Data Architects
  • Technical Consultants
  • Research Analysts


Learning Objectives - What you will Learn in this Azure Databricks with Pyspark?

Introduction

The Azure Databricks with PySpark course equips students with the skills to harness the power of Apache Spark within the Azure environment, focusing on data processing and analytics using Python.

Learning Objectives and Outcomes

  • Understand the fundamentals of Azure Databricks and its architecture.
  • Learn how to create and manage Databricks workspaces and clusters.
  • Utilize PySpark for data manipulation and transformation.
  • Implement data ingestion techniques from various sources into Databricks.
  • Develop and execute Spark jobs using Python programming.
  • Analyze and visualize data using Databricks notebooks.
  • Optimize Spark applications for performance and resource management.
  • Explore advanced PySpark features including machine learning libraries.
  • Integrate Azure Databricks with other Azure services.
  • Work on real-world data projects to solidify learning and practical application.

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